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Record W1967551973 · doi:10.1177/1073858414558065

Androgen Modulation of Hippocampal Structure and Function

2014· review· en· W1967551973 on OpenAlexaff
Sarah Atwi, Dallan McMahon, Helen E. Scharfman, Neil J. MacLusky

Bibliographic record

VenueThe Neuroscientist · 2014
Typereview
Languageen
FieldMedicine
TopicHypothalamic control of reproductive hormones
Canadian institutionsUniversity of Guelph
FundersNational Institute of Neurological Disorders and Stroke
KeywordsHippocampal formationNeuroscienceLong-term potentiationSynaptic plasticityNeurotrophic factorsNeurotransmissionAndrogenNeuroplasticityHippocampusEndocrinologyBrain-derived neurotrophic factorPsychologyInternal medicineBiologyReceptorMedicineHormone

Abstract

fetched live from OpenAlex

Androgens have profound effects on hippocampal structure and function, including induction of spines and spine synapses on the dendrites of CA1 pyramidal neurons, as well as alterations in long-term synaptic plasticity (LTP) and hippocampally dependent cognitive behaviors. How these effects occur remains largely unknown. Emerging evidence, however, suggests that one of the key elements in the response mechanism may be modulation of brain-derived neurotrophic factor (BDNF) in the mossy fiber (MF) system. In male rats, orchidectomy increases synaptic transmission and excitability in the MF pathway. Testosterone reverses these effects, suggesting that testosterone exerts tonic suppression on MF BDNF levels. These findings suggest that changes in hippocampal function resulting from declining androgen levels may reflect the outcome of responses mediated through normally balanced, but opposing, mechanisms: loss of androgen effects on the hippocampal circuitry may be compensated, at least in part, by an increase in BDNF-dependent MF plasticity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.298
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations82
Published2014
Admission routes1
Has abstractyes

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Same venueThe NeuroscientistSame topicHypothalamic control of reproductive hormonesFrench-language works237,207